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003 DE-He213
005 20240423130051.0
007 cr nn 008mamaa
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020 _a9783540322634
_9978-3-540-32263-4
024 7 _a10.1007/b105582
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aAmbient Intelligence for Scientific Discovery
_h[electronic resource] :
_bFoundations, Theories, and Systems /
_cedited by Yang Cai.
250 _a1st ed. 2005.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2005.
300 _aXIV, 314 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v3345
505 0 _aNew Paradigms in Scientific Discovery -- Science at the Speed of Thought -- Computational Biology and Language -- Interactive Comprehensible Data Mining -- Scientific Discovery Within Data Streams -- Ambient Cognition -- Shape as Memory Storage -- Spatial Cues in 3D Visualization -- Textual Genre Analysis and Identification -- Cognitive Artifacts in Complex Work -- Ambient Intelligence Systems -- Multi-modal Interaction in Biomedicine -- Continuous Body Monitoring -- Ambient Diagnostics -- Wireless Local Area Network Positioning -- Behavior-Based Indoor Navigation -- Ambient Intelligence Through Agile Agents.
520 _aMany difficult scientific discovery tasks can only be solved in interactive ways, by combining intelligent computing techniques with intuitive and adaptive user interfaces. It is inevitable to use human intelligence in scientific discovery systems: human eyes can capture complex patterns and relationships, along with detecting the exceptional cases in a data set; the human brain can easily manipulate perceptions to make decisions. Ambient intelligence is about this kind of ubiquitous and autonomous human interaction with information. Scientific discovery is a process of creative perception and communication, dealing with questions like: how do we significantly reduce information while maintaining meaning, or how do we extract patterns from massive data and growing data resources. Originating from the SIGCHI Workshop on Ambient Intelligence for Scientific Discovery, this state-of-the-art survey is organized in three parts: new paradigms in scientific discovery, ambient cognition, and ambient intelligence systems. Many chapters share common features such as interaction, vision, language, and biomedicine.
650 0 _aArtificial intelligence.
650 0 _aApplication software.
650 0 _aUser interfaces (Computer systems).
650 0 _aHuman-computer interaction.
650 0 _aDatabase management.
650 0 _aComputer graphics.
650 0 _aComputer networks .
650 1 4 _aArtificial Intelligence.
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aUser Interfaces and Human Computer Interaction.
650 2 4 _aDatabase Management.
650 2 4 _aComputer Graphics.
650 2 4 _aComputer Communication Networks.
700 1 _aCai, Yang.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540244660
776 0 8 _iPrinted edition:
_z9783540807360
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v3345
856 4 0 _uhttps://doi.org/10.1007/b105582
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cSPRINGER
999 _c184679
_d184679